1. Field of the Invention
Embodiments described herein relate generally to an image analysis device, and a control method of an image analysis device.
2. Description of the Related Art
MRI is an imaging method which magnetically excites nuclear spin of an object (a patient) placed in a static magnetic field with an RF pulse having the Larmor frequency and reconstructs an image on the basis of MR signals generated due to the excitation. The aforementioned MRI means magnetic resonance imaging, the RF pulse means a radio frequency pulse, and the MR signal means a nuclear magnetic resonance signal.
In MRI, a perfusion analysis software for analyzing blood flow volume is known. For example, if image data of a plurality of images obtained by dynamic imaging with administration of contrast medium or the like are inputted, local blood flow volume is calculated by the perfusion analysis software on the basis of the respective pixel values of the plurality of images. The above dynamic imaging is an imaging method in which time-series images are obtained from the same cross-section over a plurality of time phases.
Each pixel value of MRI approximately corresponds to intensity of an MR signal detected in each pixel position, and is not linearly related to concentration of contrast medium in tissue, in general. Note that, in this specification, it is assumed that “tissue” indicates regions of an object other than air and includes blood and blood vessels unless otherwise noted. Thus, in order to accurately measure blood flow volume in MRI, it is desirable to convert pixel values into values in proportional to concentration of contrast medium.
As a conventional technology related to this, the following Non-Patent Document 1 is known.    [Non-Patent Document 1] Paul S. Tofts et al., Quantitative Analysis of Dynamic Gd-DTPA Enhancement in Breast Tumors Using a Permeability Model; MRM, vol. 33, pp 564-568 (1995)
In a tissue including a lot of air such as a lung, a tissue and air are mixed in one pixel, MR signals are generated from a tissue region, and intensity of the detected MR signal becomes a value reflecting intensity of the MR signal in the tissue region.
Here, R1 value indicative of relaxation rate of contrast medium is an inverse number of longitudinal relaxation time. Thus, an R1 value of each pixel in MRI is not an average value of the corresponding pixel but a value reflecting the R1 value of the tissue region in the corresponding pixel.
Then, in MRI, the concentration of contrast medium of each pixel calculated on the basis of the gap between an R1 value before administration of contrast medium and an R1 value at each clock time after administration of contrast medium is not contrast medium amount per predetermined volume including air but close to a value of contrast medium amount per predetermined volume including only tissue regions excluding an air region.
Local blood flow volume (inflowing blood amount per predetermined volume and per unit time) calculated on the basis of R1 values in this manner is not a value per predetermined volume including air but close to a value per predetermined volume excluding air in the pixel.
On the other hand, because blood flow volume measured by other methods or devices such as an X-ray computed tomography apparatus is a value per predetermined volume including air, local blood flow volume measured by MRI becomes a greatly different value from local blood flow volume measured by other methods.
In order to provide an intelligible explanation with a concrete example, consider a pixel A consisting of 50% tissue and 50% air and a pixel B consisting of 100% tissue. In the case of an X-ray computed tomography apparatus, for example, a pixel value given by HU (Hounsfield Unit) value increases in proportion to rise of concentration of contrast medium in each pixel. It is assumed that the pixel value of the pixel A is 50 before administration of contrast medium, the pixel value of the pixel B is 100 before administration of contrast medium, and concentration of contrast medium in all the tissue regions uniformly increased by 10% at time C after administration of contrast medium.
In this case, for example, the pixel value of the pixel A becomes 55 at time C, the pixel value of the pixel B becomes 110 at time C, the pixel A indicates 5 of contrast medium inflow per predetermined volume and per predetermined time, and the pixel B indicates 10 of contrast medium inflow per predetermined volume and per predetermined time. That is, the blood flow volume (corresponding to increment of concentration of contrast medium per predetermined volume and per predetermined time) measured by an X-ray computed tomography apparatus is a value per predetermined volume including air, and the blood flow volume of the pixel B is measured as a double value of the blood flow volume of the pixel A.
On the other hand, because concentration of contrast medium in accordance with the gap between an R1 value before administration of contrast medium and an R1 value at each clock time after administration of contrast medium is calculated in MRI, an air region of the pixel A has no influence on the measurement. Thus, both the pixel A and pixel B are commonly calculated that 10 of contrast medium are flowed in per predetermined volume and per predetermined time at time C after administration of contrast medium. In order to avoid confusion, it is preferable that local blood flow volume calculated in MRI becomes a value similar to local blood flow volume measured by other methods.
Therefore, a novel technology to calculate a value close to local blood flow volume per predetermined volume including air in an object by correcting non-linearity between a signal value and concentration of contrast medium in the case of calculating local blood flow volume in MRI has been desired.